State space and noise models of a signal

Hello
I would like to apply Kalman filter to the signal in the attached file. I am asking how to generate the required matrices for the space state and noise models, which I should input to the filter.
It is my first exposure to this subject,and I much appreciate simple explanations and a practical help.
Thank you
Attachments:
Signal 2.xlsx ‏10 KB

Yeah, unfortunately I don't think I'll be able to make it down to Austin for the conference.
But more importantly, I don’t think I completely solved my curve fitting problem.  The curve fitting vi that I am using isn’t generating the output that I was expecting.  My goal is to simply add noise to a signal, then reconstruct the signal finding the best fit line/curve, which best represents the original signal.  Here is where I currently stand:
The frequency of the new graph is too high.  A sinc function is produced, but it doesn’t share the same form as the original signal. 
I've tried other options, such as the Levenberg-Marquardt method, but this is proving to be a bit difficult to understand.  I will attach the curve_fitting.vi and the Levenberg-Marquardt example that I was looking at.  I think the LM vi is very close to what I need, but I’m having trouble integrating my own numbers into the program, to generate the results that I need.  If anyone has any advice with the curve fitting, or any information that might 'dumb-down' some of the sub vi's in the Levenberg-Marquardt program model, it would help me out.
Attachments:
SimpleFit.zip ‏147 KB
curve_fitting.vi ‏163 KB

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